Scientific Agent Skills
by @k-dense-ai · plugin · 149 skills
Scientific Agent Skills from K-Dense-AI/scientific-agent-skills.
Install the whole plugin (CLI)
npx skillmds add k-dense-ai/esm
npx skillmds add k-dense-ai/pdf
npx skillmds add k-dense-ai/aeon
npx skillmds add k-dense-ai/bids
npx skillmds add k-dense-ai/dask
npx skillmds add k-dense-ai/cirq
npx skillmds add k-dense-ai/gget
npx skillmds add k-dense-ai/pptx
npx skillmds add k-dense-ai/docx
npx skillmds add k-dense-ai/pymc
npx skillmds add k-dense-ai/shap
npx skillmds add k-dense-ai/vaex
npx skillmds add k-dense-ai/xlsx
npx skillmds add k-dense-ai/gtars
npx skillmds add k-dense-ai/modal
npx skillmds add k-dense-ai/pymoo
npx skillmds add k-dense-ai/arbor
npx skillmds add k-dense-ai/pysam
npx skillmds add k-dense-ai/pytdc
npx skillmds add k-dense-ai/qutip
npx skillmds add k-dense-ai/rdkit
npx skillmds add k-dense-ai/rowan
npx skillmds add k-dense-ai/simpy
npx skillmds add k-dense-ai/depmap
npx skillmds add k-dense-ai/flowio
npx skillmds add k-dense-ai/geniml
npx skillmds add k-dense-ai/pathml
npx skillmds add k-dense-ai/sympy
npx skillmds add k-dense-ai/polars
npx skillmds add k-dense-ai/qiskit
npx skillmds add k-dense-ai/scanpy
npx skillmds add k-dense-ai/scvelo
npx skillmds add k-dense-ai/matlab
npx skillmds add k-dense-ai/adaptyv
npx skillmds add k-dense-ai/anndata
npx skillmds add k-dense-ai/astropy
npx skillmds add k-dense-ai/cobrapy
npx skillmds add k-dense-ai/datamol
npx skillmds add k-dense-ai/lamindb
npx skillmds add k-dense-ai/matchms
npx skillmds add k-dense-ai/medchem
npx skillmds add k-dense-ai/molfeat
npx skillmds add k-dense-ai/onekgpd
npx skillmds add k-dense-ai/primekg
npx skillmds add k-dense-ai/pydicom
npx skillmds add k-dense-ai/seaborn
npx skillmds add k-dense-ai/arboreto
npx skillmds add k-dense-ai/deepchem
npx skillmds add k-dense-ai/diffdock
npx skillmds add k-dense-ai/fluidsim
npx skillmds add k-dense-ai/histolab
npx skillmds add k-dense-ai/networkx
npx skillmds add k-dense-ai/nextflow
npx skillmds add k-dense-ai/pi-agent
npx skillmds add k-dense-ai/pydeseq2
npx skillmds add k-dense-ai/pyhealth
npx skillmds add k-dense-ai/pymatgen
npx skillmds add k-dense-ai/pyopenms
npx skillmds add k-dense-ai/pyzotero
npx skillmds add k-dense-ai/tamarind
npx skillmds add k-dense-ai/autoskill
npx skillmds add k-dense-ai/biopython
npx skillmds add k-dense-ai/deeptools
npx skillmds add k-dense-ai/geomaster
npx skillmds add k-dense-ai/geopandas
npx skillmds add k-dense-ai/hypogenic
npx skillmds add k-dense-ai/liteparse
npx skillmds add k-dense-ai/neurokit2
npx skillmds add k-dense-ai/pennylane
npx skillmds add k-dense-ai/pufferlib
npx skillmds add k-dense-ai/tiledbvcf
npx skillmds add k-dense-ai/torchdrug
npx skillmds add k-dense-ai/etetoolkit
npx skillmds add k-dense-ai/exa-search
npx skillmds add k-dense-ai/markitdown
npx skillmds add k-dense-ai/matplotlib
npx skillmds add k-dense-ai/pacsomatic
npx skillmds add k-dense-ai/paperzilla
npx skillmds add k-dense-ai/polars-bio
npx skillmds add k-dense-ai/pylabrobot
npx skillmds add k-dense-ai/scikit-bio
npx skillmds add k-dense-ai/scvi-tools
npx skillmds add k-dense-ai/umap-learn
npx skillmds add k-dense-ai/bioservices
npx skillmds add k-dense-ai/bulk-rnaseq
npx skillmds add k-dense-ai/peer-review
npx skillmds add k-dense-ai/statsmodels
npx skillmds add k-dense-ai/zarr-python
npx skillmds add k-dense-ai/infographics
npx skillmds add k-dense-ai/paper-lookup
npx skillmds add k-dense-ai/parallel-web
npx skillmds add k-dense-ai/scikit-learn
npx skillmds add k-dense-ai/transformers
npx skillmds add k-dense-ai/usfiscaldata
npx skillmds add k-dense-ai/latex-posters
npx skillmds add k-dense-ai/open-notebook
npx skillmds add k-dense-ai/phylogenetics
npx skillmds add k-dense-ai/pptx-posters
npx skillmds add k-dense-ai/dhdna-profiler
npx skillmds add k-dense-ai/generate-image
npx skillmds add k-dense-ai/what-if-oracle
npx skillmds add k-dense-ai/database-lookup
npx skillmds add k-dense-ai/hugging-science
npx skillmds add k-dense-ai/research-grants
npx skillmds add k-dense-ai/research-lookup
npx skillmds add k-dense-ai/scikit-survival
npx skillmds add k-dense-ai/torch-geometric
npx skillmds add k-dense-ai/treatment-plans
npx skillmds add k-dense-ai/venue-templates
npx skillmds add k-dense-ai/cellxgene-census
npx skillmds add k-dense-ai/clinical-reports
npx skillmds add k-dense-ai/ginkgo-cloud-lab
npx skillmds add k-dense-ai/glycoengineering
npx skillmds add k-dense-ai/optimize-for-gpu
npx skillmds add k-dense-ai/bgpt-paper-search
npx skillmds add k-dense-ai/literature-review
npx skillmds add k-dense-ai/omero-integration
npx skillmds add k-dense-ai/pytorch-lightning
npx skillmds add k-dense-ai/scientific-slides
npx skillmds add k-dense-ai/stable-baselines3
npx skillmds add k-dense-ai/statistical-power
npx skillmds add k-dense-ai/molecular-dynamics
npx skillmds add k-dense-ai/pathway-enrichment
npx skillmds add k-dense-ai/scholar-evaluation
npx skillmds add k-dense-ai/scientific-writing
npx skillmds add k-dense-ai/citation-management
npx skillmds add k-dense-ai/experimental-design
npx skillmds add k-dense-ai/timesfm-forecasting
npx skillmds add k-dense-ai/dnanexus-integration
npx skillmds add k-dense-ai/imaging-data-commons
npx skillmds add k-dense-ai/latchbio-integration
npx skillmds add k-dense-ai/neuropixels-analysis
npx skillmds add k-dense-ai/benchling-integration
npx skillmds add k-dense-ai/consciousness-council
npx skillmds add k-dense-ai/hypothesis-generation
npx skillmds add k-dense-ai/opentrons-integration
npx skillmds add k-dense-ai/scientific-schematics
npx skillmds add k-dense-ai/labarchive-integration
npx skillmds add k-dense-ai/get-available-resources
npx skillmds add k-dense-ai/statistical-analysis
npx skillmds add k-dense-ai/iso-13485-certification
npx skillmds add k-dense-ai/market-research-reports
npx skillmds add k-dense-ai/protocolsio-integration
npx skillmds add k-dense-ai/markdown-mermaid-writing
npx skillmds add k-dense-ai/scientific-brainstorming
npx skillmds add k-dense-ai/scientific-visualization
npx skillmds add k-dense-ai/clinical-decision-support
npx skillmds add k-dense-ai/exploratory-data-analysis
npx skillmds add k-dense-ai/scientific-critical-thinkingSkills in this plugin
- ▌ esm · k-dense-ai bundleGenerate, predict, and embed protein sequences and structures using ESM3, ESMC, and ESMFold2 with local or cloud inference.
- ▌ pdf · k-dense-ai bundleRead, extract, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python libraries and command-line tools.
- ▌ aeon · k-dense-ai bundlePerform time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using a scikit-learn compatible Python toolkit.
- ▌ bids · k-dense-ai bundleOrganize, query, validate, and convert neuroscience and biomedical data using the Brain Imaging Data Structure (BIDS) standard.
- ▌ dask · k-dense-ai bundleScale pandas and NumPy workflows to larger-than-memory datasets using parallel and distributed computing.
- ▌ cirq · k-dense-ai bundleDesign, simulate, and run quantum circuits on Google Quantum AI hardware and partner backends using Cirq.
- ▌ gget · k-dense-ai bundleQuery 20+ bioinformatics databases from the command line or Python for gene information, sequences, protein structures, enrichment analysis, and more.
- ▌ pptx · k-dense-ai bundleCreate, read, edit, and convert .pptx presentations with design guidance, template manipulation, and visual QA workflows.
- ▌ docx · k-dense-ai bundleCreate, read, edit, and manipulate Word documents (.docx) with formatting, tables, images, and tracked changes.
- ▌ pymc · k-dense-ai bundleBuild, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.
- ▌ shap · k-dense-ai bundleExplain machine learning model predictions using SHAP values, compute feature importance, and generate visualizations including waterfall, beeswarm, bar, scatter, force, and heatmap plots.
- ▌ vaex · k-dense-ai bundleProcess and analyze large tabular datasets (billions of rows) that exceed available RAM using lazy, out-of-core DataFrames with fast aggregations, visualization, and machine learning integration.
- ▌ xlsx · k-dense-ai bundleCreate, edit, analyze, or convert Excel spreadsheets (.xlsx, .xlsm) with formulas, formatting, financial models, and multi-sheet workbooks.
- ▌ gtars · k-dense-ai bundleHigh-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
- ▌ modal · k-dense-ai bundleDeploy and serve AI/ML models on Modal's serverless cloud platform with on-demand GPUs, autoscaling containers, persistent storage, and scheduled jobs.
- ▌ pymoo · k-dense-ai bundleSolve single and multi-objective optimization problems using NSGA-II/III, MOEA/D, and other evolutionary algorithms with customizable operators, constraint handling, and benchmark problems.
- ▌ arbor · k-dense-ai bundleRun autonomous optimization loops that iteratively improve artifacts against evaluators using hypothesis tree refinement, without overfitting.
- ▌ pysam · k-dense-ai bundleRead, write, and manipulate genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.
- ▌ pytdc · k-dense-ai bundleAccess AI-ready drug discovery datasets and benchmarks from Therapeutics Data Commons, covering ADME, toxicity, drug-target interactions, and molecular generation with standardized splits and evaluation metrics.
- ▌ qutip · k-dense-ai bundleSimulate and analyze open quantum systems using QuTiP, including master equations, Lindblad dynamics, decoherence, and quantum optics.
- ▌ rdkit · k-dense-ai bundlePerform cheminformatics tasks including molecular I/O, descriptor calculation, fingerprinting, substructure search, and similarity analysis using the RDKit library.
- ▌ rowan · k-dense-aiRun cloud-native molecular modeling and drug-design workflows including pKa prediction, docking, molecular dynamics, and protein-ligand cofolding via a Python API.
- ▌ simpy · k-dense-ai bundleBuild discrete-event simulations of systems with processes, queues, resources, and time-based events using SimPy in Python.
- ▌ depmap · k-dense-ai bundleQuery the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.
- ▌ flowio · k-dense-ai bundleParse FCS (Flow Cytometry Standard) files v2.0-3.1, extract events as NumPy arrays, read metadata and channels, and convert to CSV or DataFrame for flow cytometry data preprocessing.
- ▌ geniml · k-dense-ai bundleTrain unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.
- ▌ pathml · k-dense-ai bundleAnalyze whole-slide pathology images with Python: load 160+ slide formats, preprocess H&E stains, segment nuclei, construct spatial graphs, train ML models, and process multiplex immunofluorescence data (CODEX, Vectra).
- ▌ sympy · k-dense-ai bundlePerform exact symbolic mathematics in Python — algebra, calculus, equation solving, symbolic linear algebra, and code generation via lambdify or LaTeX.
- ▌ polars · k-dense-ai bundleProcess data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.
- ▌ qiskit · k-dense-ai bundleBuild and execute quantum circuits on IBM Quantum hardware, simulators, and third-party providers using the Qiskit framework.
- ▌ scanpy · k-dense-ai bundleRun standard single-cell RNA-seq analysis pipelines: QC, normalization, dimensionality reduction, clustering, differential expression, and visualization using Scanpy.
- ▌ scvelo · k-dense-ai bundleEstimate cell state transitions from unspliced/spliced mRNA dynamics using scVelo, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data.
- ▌ matlab · k-dense-ai bundlePerform numerical computing, matrix operations, data analysis, and scientific visualization using MATLAB or GNU Octave.
- ▌ adaptyv · k-dense-ai bundleSubmit protein sequences to the Adaptyv Bio Foundry for experimental characterization (binding, thermostability, expression, fluorescence) and retrieve results via API or Python SDK.
- ▌ anndata · k-dense-ai bundleCreate, read, manipulate, and store annotated data matrices using the AnnData Python package, designed for single-cell genomics and general-purpose annotated data workflows.
- ▌ astropy · k-dense-ai bundlePerform astronomical data analysis with Astropy: coordinate transformations, unit conversions, FITS I/O, cosmological calculations, time handling, table operations, and WCS transformations.
- ▌ cobrapy · k-dense-ai bundlePerform constraint-based metabolic modeling with COBRApy: run FBA, FVA, gene knockouts, flux sampling, and manage SBML models for systems biology and metabolic engineering.
- ▌ datamol · k-dense-ai bundleSimplify molecular cheminformatics with a Pythonic wrapper around RDKit for SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing.
- ▌ lamindb · k-dense-ai bundleManage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.
- ▌ matchms · k-dense-ai bundleProcess and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.
- ▌ medchem · k-dense-ai bundleApply medicinal chemistry filters for compound triage: drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and a custom query language for library filtering.
- ▌ molfeat · k-dense-ai bundleConvert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.
- ▌ onekgpd · k-dense-ai bundleQuery the 1000 Genomes Project dataset at the individual participant level to find variants, carriers, and relatedness information.
- ▌ primekg · k-dense-ai bundleQuery the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological data including genes, drugs, diseases, phenotypes, and more.
- ▌ pydicom · k-dense-ai bundleRead, write, and modify DICOM medical imaging files, including pixel data extraction, metadata manipulation, anonymization, and format conversion.
- ▌ seaborn · k-dense-ai bundleCreate publication-quality statistical graphics with dataset-oriented plotting, multivariate analysis, and automatic statistical estimation using minimal code.
- ▌ arboreto · k-dense-ai bundleInfer gene regulatory networks from gene expression data using scalable algorithms (GRNBoost2, GENIE3) with support for distributed computation.
- ▌ deepchem · k-dense-ai bundlePredict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.
- ▌ diffdock · k-dense-ai bundlePredict 3D binding poses of small molecule ligands to protein targets using diffusion-based molecular docking, supporting single complexes, batch processing, and virtual screening.
- ▌ fluidsim · k-dense-ai bundleRun computational fluid dynamics simulations using Python, including Navier-Stokes equations, shallow water, and stratified flows with pseudospectral methods and HPC support.
- ▌ histolab · k-dense-ai bundleProcess whole slide images for digital pathology: detect tissue, extract tiles, and prepare datasets for deep learning pipelines.
- ▌ networkx · k-dense-ai bundleCreate, analyze, and visualize complex networks and graphs in Python with NetworkX, including graph algorithms, community detection, synthetic network generation, and multiple I/O formats.
- ▌ nextflow · k-dense-ai bundleBuild, run, and debug Nextflow data pipelines and nf-core workflows end to end, covering processes, channels, operators, configuration, testing, and deployment to HPC or cloud.
- ▌ pi-agent · k-dense-ai bundleInstall, configure, and extend Pi, a terminal coding harness, with support for custom providers, models, extensions, skills, packages, themes, SDK integration, RPC mode, JSON event streams, and ecosystem packages for subagent delegation, MCP servers, interactive forms, and web access.
- ▌ pydeseq2 · k-dense-ai bundlePerform differential gene expression analysis for bulk RNA-seq data using PyDESeq2, supporting formulaic designs, Wald tests, FDR correction, LFC shrinkage, and result visualization.
- ▌ pyhealth · k-dense-ai bundleBuild clinical deep-learning pipelines with PyHealth: load EHR, signal, and imaging datasets, define prediction tasks, instantiate models, train with the PyHealth Trainer, and compute clinical metrics.
- ▌ pymatgen · k-dense-ai bundleAnalyze and manipulate crystal structures, compute phase diagrams, and access the Materials Project database using the pymatgen library.
- ▌ pyopenms · k-dense-ai bundleAnalyze proteomics and metabolomics mass spectrometry data with PyOpenMS: read/write MS file formats, process spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines using ready-to-run scripts.
- ▌ pyzotero · k-dense-ai bundleManage Zotero reference libraries programmatically using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3.
- ▌ tamarind · k-dense-ai bundleRun computational biology tools for protein structure prediction, design, docking, and molecular dynamics on managed cloud GPUs via REST API or MCP server.
- ▌ autoskill · k-dense-ai bundleAnalyze recent screen activity via a local screenpipe daemon, detect repeated research workflows, and draft new skills or composition recipes for uncovered patterns.
- ▌ biopython · k-dense-ai bundleManipulate biological sequences, parse FASTA/GenBank/PDB files, access NCBI databases, run BLAST searches, and perform phylogenetics using the Biopython library.
- ▌ deeptools · k-dense-ai bundleProcess and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.
- ▌ geomaster · k-dense-ai bundleProcess satellite imagery, perform GIS analysis, and apply spatial machine learning across 70+ geospatial topics with code examples in 8 programming languages.
- ▌ geopandas · k-dense-ai bundleExtends pandas for geospatial vector data analysis, including reading/writing shapefiles, GeoJSON, GeoPackage, and PostGIS, performing spatial joins, geometric operations, coordinate transformations, and creating static or interactive maps.
- ▌ hypogenic · k-dense-ai bundleAutomates hypothesis generation and testing on tabular datasets using LLMs, combining data-driven discovery with literature integration for scientific research.
- ▌ liteparse · k-dense-ai bundleParse PDFs, Office files, and images locally with layout-preserved text, bounding boxes, OCR, and page screenshots for RAG and multimodal agents.
- ▌ neurokit2 · k-dense-ai bundleProcess and analyze physiological signals including ECG, EEG, EDA, RSP, PPG, EMG, and EOG using Python.
- ▌ pennylane · k-dense-ai bundleTrain quantum circuits like neural networks with automatic differentiation, device-independent programming, and integration with PyTorch or JAX.
- ▌ pufferlib · k-dense-ai bundleTrain reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.
- ▌ tiledbvcf · k-dense-aiStore, query, and export genomic variant data (VCF/BCF) using TileDB's sparse array technology for scalable population genomics workflows.
- ▌ torchdrug · k-dense-ai bundleBuild and train graph neural networks for drug discovery, protein modeling, and molecular science using PyTorch-native tools.
- ▌ etetoolkit · k-dense-ai bundleManipulate phylogenetic trees, detect evolutionary events, integrate NCBI taxonomy, and create publication-quality visualizations using the ETE toolkit.
- ▌ exa-search · k-dense-ai bundleSearch the web and extract content from URLs using Exa, with support for academic and scientific sources.
- ▌ markitdown · k-dense-ai bundleConvert files and office documents to Markdown using Microsoft's MarkItDown tool. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
- ▌ matplotlib · k-dense-ai bundleCreate publication-quality static, animated, and interactive plots with fine-grained control over every element using Matplotlib's pyplot and object-oriented APIs.
- ▌ pacsomatic · k-dense-ai bundleValidates inputs, generates samplesheets and launch scripts, and optionally executes nf-core/pacsomatic matched tumor-normal workflows from BAM files, supporting local runs and scheduler submission (LSF/Slurm/PBS/SGE).
- ▌ paperzilla · k-dense-aiChat with your agent about projects, recommendations, and canonical papers in Paperzilla. Fetch feeds, read papers, leave feedback, and export data using the pz CLI.
- ▌ polars-bio · k-dense-ai bundlePerform high-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames, including overlap, nearest, merge, coverage, complement, subtract, and reading/writing BED, VCF, BAM, GFF, FASTA, and FASTQ formats with streaming and cloud-native support.
- ▌ pylabrobot · k-dense-ai bundleControl liquid handling robots, plate readers, pumps, and other lab equipment through a unified Python interface across platforms.
- ▌ scikit-bio · k-dense-ai bundleAnalyze biological sequences, alignments, phylogenetic trees, and diversity metrics (alpha/beta, UniFrac) with ordination (PCoA) and PERMANOVA for microbiome and community ecology data.
- ▌ scvi-tools · k-dense-ai bundleProvides deep generative models for single-cell omics analysis, including probabilistic batch correction, transfer learning, differential expression, and multi-modal integration.
- ▌ umap-learn · k-dense-ai bundlePerform nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows using the umap-learn library.
- ▌ bioservices · k-dense-ai bundleQuery 40+ bioinformatics services (UniProt, KEGG, ChEMBL, Reactome) with a unified Python interface for cross-database analysis, identifier mapping, and sequence analysis.
- ▌ bulk-rnaseq · k-dense-ai bundleOrchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.
- ▌ peer-review · k-dense-ai bundleEvaluate scientific manuscripts and grant proposals with structured, checklist-based peer review covering methodology, statistics, reproducibility, ethics, and reporting standards.
- ▌ statsmodels · k-dense-ai bundleFit statistical models (OLS, GLM, ARIMA, mixed models) with detailed diagnostics, residuals, and inference for econometrics and time series analysis.
- ▌ zarr-python · k-dense-ai bundleStore and process large N-dimensional arrays with chunking, compression, and parallel I/O, integrating with NumPy, Dask, and Xarray for cloud-native scientific computing.
- ▌ infographics · k-dense-ai bundleGenerate publication-quality infographics using Nano Banana Pro AI with Gemini 3 Pro quality review and optional Perplexity Sonar research. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
- ▌ paper-lookup · k-dense-ai bundleSearch 10 academic literature APIs for papers, preprints, citations, and open-access full text with reproducible provenance.
- ▌ parallel-web · k-dense-ai bundleSearch the web, extract URL content, enrich datasets with web-sourced fields, and run deep research reports, prioritizing academic and scientific sources.
- ▌ scikit-learn · k-dense-ai bundleBuild and evaluate machine learning models using scikit-learn for classification, regression, clustering, dimensionality reduction, and preprocessing.
- ▌ transformers · k-dense-ai bundleLoad pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.
- ▌ usfiscaldata · k-dense-ai bundleQuery the U.S. Treasury Fiscal Data REST API for federal financial data including national debt, daily and monthly treasury statements, securities auctions, interest rates, exchange rates, savings bonds, and government revenue and spending statistics. No API key required.
- ▌ latex-posters · k-dense-ai bundleCreate professional research posters in LaTeX using beamerposter, tikzposter, or baposter with layout design, color schemes, multi-column formats, and figure integration.
- ▌ open-notebook · k-dense-ai bundleSelf-host an open-source research notebook with AI-powered note generation, multi-speaker podcast creation, and context-aware document chat, supporting 16+ AI providers.
- ▌ phylogenetics · k-dense-ai bundleBuild and analyze phylogenetic trees using MAFFT, IQ-TREE 2, and FastTree, with visualization via ETE3 or FigTree for evolutionary analysis, microbial genomics, viral phylodynamics, and molecular clock studies.
- ▌ pptx-posters · k-dense-ai bundleCreate research posters using HTML/CSS that can be exported to PDF or PPTX, with AI-generated visual elements and responsive layouts.
- ▌ dhdna-profiler · k-dense-ai bundleAnalyze any text to extract a cognitive fingerprint across 12 dimensions, revealing reasoning patterns, decision styles, and thinking signatures.
- ▌ generate-image · k-dense-ai bundleGenerate and edit high-quality images using OpenRouter's AI models including FLUX.2 Pro and Gemini 3.1 Flash Image Preview.
- ▌ what-if-oracle · k-dense-ai bundleRun structured What-If scenario analysis with 4-6 branch possibility exploration (best, likely, worst, wild card, contrarian, second-order). Use for speculative questions about uncertain futures, strategic forks, contingency planning, or stress-testing decisions.
- ▌ database-lookup · k-dense-ai bundleQuery documented public database APIs with explicit endpoints, filters, pagination, and provenance for reproducible retrieval of scientific, regulatory, or financial facts.
- ▌ hugging-science · k-dense-ai bundleDiscovers and uses scientific datasets, models, blog posts, and interactive demos from a curated catalog for AI/ML work in domains like biology, chemistry, physics, and genomics.
- ▌ research-grants · k-dense-ai bundleWrite competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC with agency-specific formatting, review criteria, budget preparation, and compliance guidance.
- ▌ research-lookup · k-dense-ai bundleLook up current research and scientific information across three backends: fast web search, deep multi-source synthesis, and scholarly paper searches. Automatically routes each query to the best backend and saves every result for reproducible citation.
- ▌ scikit-survival · k-dense-ai bundlePerform survival analysis and time-to-event modeling in Python using scikit-survival, including Cox models, random survival forests, gradient boosting, survival SVMs, and evaluation metrics like concordance index and Brier score.
- ▌ torch-geometric · k-dense-ai bundleBuild and train graph neural networks with PyTorch Geometric, covering node/link/graph classification, message passing layers, heterogeneous graphs, and custom datasets.
- ▌ treatment-plans · k-dense-ai bundleGenerate concise (3-4 page) medical treatment plans in LaTeX/PDF format across all clinical specialties, with SMART goals, evidence-based interventions, and HIPAA compliance.
- ▌ venue-templates · k-dense-ai bundleAccess comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues, academic conferences, research posters, and grant proposals.
- ▌ cellxgene-census · k-dense-ai bundleQuery the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data, enabling efficient access to cell metadata, gene expression slices, summary counts, and embeddings without downloading whole datasets.
- ▌ clinical-reports · k-dense-ai bundleGenerate comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports, clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries) with templates, regulatory compliance, and validation tools.
- ▌ ginkgo-cloud-lab · k-dense-ai bundleSubmit and manage protocols on Ginkgo Bioworks Cloud Lab for autonomous lab execution, including protein expression, purification, quantification, RNA synthesis, and custom workflows via EstiMate.
- ▌ glycoengineering · k-dense-ai bundleAnalyze and engineer protein glycosylation by scanning sequences for N-glycosylation sequons, predicting O-glycosylation hotspots, and accessing curated glycoengineering tools for therapeutic antibody optimization and vaccine design.
- ▌ optimize-for-gpu · k-dense-ai bundleGPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, and other RAPIDS libraries for dramatic speedups on numerical, data, ML, graph, and simulation workloads.
- ▌ bgpt-paper-search · k-dense-aiSearch scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions.
- ▌ literature-review · k-dense-ai bundleConduct systematic literature reviews by searching multiple academic databases, synthesizing findings, and generating professionally formatted documents with verified citations.
- ▌ omero-integration · k-dense-ai bundleAccess microscopy images and metadata via the OMERO Python API: retrieve datasets, analyze pixels, manage ROIs and annotations, and batch-process for high-content screening workflows.
- ▌ pytorch-lightning · k-dense-ai bundleOrganize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.
- ▌ scientific-slides · k-dense-ai bundleBuild visually engaging scientific slide decks for conferences, seminars, defenses, and research talks with structured planning, design templates, and automated image generation.
- ▌ stable-baselines3 · k-dense-ai bundleTrain reinforcement learning agents using PPO, SAC, DQN, TD3, DDPG, and A2C algorithms with a scikit-learn-like API. Supports custom Gymnasium environments, vectorized environments, callbacks, and model persistence.
- ▌ statistical-power · k-dense-ai bundleCalculate sample sizes, minimum detectable effects, and power curves for study planning using closed-form formulas or Monte Carlo simulation.
- ▌ molecular-dynamics · k-dense-ai bundleRun and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, run energy minimization and production MD, analyze trajectories (RMSD, RMSF, contact maps, free energy surfaces).
- ▌ pathway-enrichment · k-dense-ai bundleRun pathway and gene-set enrichment analysis on gene lists or ranked gene data, then interpret the results. Covers over-representation analysis (ORA), Gene Set Enrichment Analysis (GSEA), and single-sample scoring using gseapy, g:Profiler, and Enrichr libraries.
- ▌ scholar-evaluation · k-dense-ai bundleSystematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
- ▌ scientific-writing · k-dense-ai bundleWrite scientific manuscripts in full paragraphs using IMRAD structure, with citations (APA/AMA/Vancouver), figures/tables, and reporting guidelines (CONSORT/STROBE/PRISMA) for research papers and journal submissions.
- ▌ citation-management · k-dense-ai bundleSearch Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries.
- ▌ experimental-design · k-dense-ai bundleDesign experiments and studies before data collection — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable.
- ▌ timesfm-forecasting · k-dense-ai bundleForecast any univariate time series (sales, sensors, energy, vitals, weather) zero-shot using Google's TimesFM foundation model, with point forecasts and prediction intervals from CSV, DataFrame, or array inputs.
- ▌ dnanexus-integration · k-dense-ai bundleBuild and deploy apps/applets on the DNAnexus cloud genomics platform, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.
- ▌ imaging-data-commons · k-dense-ai bundleQuery and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
- ▌ latchbio-integration · k-dense-ai bundleBuild and deploy bioinformatics workflows as serverless pipelines on the Latch platform using Python decorators, cloud data management, and GPU support.
- ▌ neuropixels-analysis · k-dense-ai bundleAnalyze Neuropixels extracellular recordings end-to-end with SpikeInterface, covering loading, preprocessing, drift correction, spike sorting, quality metrics, and unit curation.
- ▌ benchling-integration · k-dense-ai bundleIntegrate with Benchling's Python SDK and REST API to manage registry entities, inventory, ELN entries, workflows, and Data Warehouse queries for life sciences R&D automation.
- ▌ consciousness-council · k-dense-ai bundleSimulates a multi-perspective deliberation council to explore complex questions, decisions, or creative challenges from diverse thinking archetypes.
- ▌ hypothesis-generation · k-dense-ai bundleFormulate testable hypotheses from observations, design experiments, and generate predictions using a structured scientific method framework.
- ▌ opentrons-integration · k-dense-ai bundleWrite Opentrons Protocol API v2 protocols for Flex and OT-2 robots to automate liquid handling, control hardware modules, and manage labware configurations.
- ▌ scientific-schematics · k-dense-ai bundleCreate publication-quality scientific diagrams using AI generation with smart iterative refinement and quality review.
- ▌ labarchive-integration · k-dense-ai bundleAccess and manage LabArchives electronic lab notebooks programmatically via REST API. Create entries, upload attachments, backup notebooks, generate reports, and integrate with Protocols.io, Jupyter, REDCap, and other scientific tools.
- ▌ get-available-resources · k-dense-ai bundleDetects available CPU, GPU, memory, and disk resources and generates strategic recommendations for scientific computing tasks.
- ▌ statistical-analysis · k-dense-ai bundleGuides statistical hypothesis testing with assumption checks, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting for research data.
- ▌ iso-13485-certification · k-dense-ai bundlePrepare ISO 13485:2016 certification documentation for medical device Quality Management Systems, including gap analysis, template-based document creation, and compliance checklists.
- ▌ market-research-reports · k-dense-ai bundleGenerate comprehensive, professional-grade market research reports (50+ pages) with LaTeX formatting, strategic frameworks, and data-driven visualizations.
- ▌ protocolsio-integration · k-dense-ai bundleIntegrates with the protocols.io API v3 to search, create, update, and publish scientific protocols, manage steps and materials, handle discussions, organize workspaces, and upload files.
- ▌ markdown-mermaid-writing · k-dense-ai bundleCreates scientific documentation using markdown with embedded Mermaid diagrams as the default format, enforcing a text-based diagram standard with style guides, 24 diagram type references, and document templates.
- ▌ scientific-brainstorming · k-dense-ai bundleGenerate novel research ideas through structured, conversational brainstorming that explores interdisciplinary connections, challenges assumptions, and identifies research gaps.
- ▌ scientific-visualization · k-dense-ai bundleCreate publication-ready scientific figures with multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and journal-specific formatting using matplotlib, seaborn, and plotly.
- ▌ clinical-decision-support · k-dense-ai bundleGenerate professional clinical decision support documents for pharmaceutical and clinical research, including biomarker-stratified cohort analyses and evidence-based treatment recommendation reports with GRADE grading, statistical analysis, and publication-ready LaTeX/PDF output.
- ▌ exploratory-data-analysis · k-dense-ai bundleAutomatically detect and analyze scientific data files across 200+ formats, generating detailed markdown reports with quality metrics and analysis recommendations.
- ▌ scientific-critical-thinking · k-dense-ai bundleEvaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.